Source code for airflow.sensors.python

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from typing import Callable, Dict, List, Optional

from airflow.sensors.base import BaseSensorOperator
from airflow.utils.operator_helpers import determine_kwargs


[docs]class PythonSensor(BaseSensorOperator): """ Waits for a Python callable to return True. User could put input argument in templates_dict e.g ``templates_dict = {'start_ds': 1970}`` and access the argument by calling ``kwargs['templates_dict']['start_ds']`` in the callable :param python_callable: A reference to an object that is callable :type python_callable: python callable :param op_kwargs: a dictionary of keyword arguments that will get unpacked in your function :type op_kwargs: dict :param op_args: a list of positional arguments that will get unpacked when calling your callable :type op_args: list :param templates_dict: a dictionary where the values are templates that will get templated by the Airflow engine sometime between ``__init__`` and ``execute`` takes place and are made available in your callable's context after the template has been applied. :type templates_dict: dict of str """
[docs] template_fields = ('templates_dict', 'op_args', 'op_kwargs')
def __init__( self, *, python_callable: Callable, op_args: Optional[List] = None, op_kwargs: Optional[Dict] = None, templates_dict: Optional[Dict] = None, **kwargs, ): super().__init__(**kwargs) self.python_callable = python_callable self.op_args = op_args or [] self.op_kwargs = op_kwargs or {} self.templates_dict = templates_dict
[docs] def poke(self, context: Dict): context.update(self.op_kwargs) context['templates_dict'] = self.templates_dict self.op_kwargs = determine_kwargs(self.python_callable, self.op_args, context) self.log.info("Poking callable: %s", str(self.python_callable)) return_value = self.python_callable(*self.op_args, **self.op_kwargs) return bool(return_value)

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